The 1998 Version of the NSWC Aeroprediction Code

The 1998 Version of the NSWC Aeroprediction Code
Author :
Publisher :
Total Pages : 129
Release :
ISBN-10 : 1423562720
ISBN-13 : 9781423562726
Rating : 4/5 (20 Downloads)

Book Synopsis The 1998 Version of the NSWC Aeroprediction Code by : Frank G. Moore

Download or read book The 1998 Version of the NSWC Aeroprediction Code written by Frank G. Moore and published by . This book was released on 1998-04-01 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: The NSWC Aero prediction code has been extended to the roll position of 45 deg (fins in 'x' or cross roll orientation) in addition to the roll position of 0 deg (fins in '+' or plus roll orientation). It has also been extended to compute aerodynamics of nonaxisymmetric bodies based on an equivalent axisymmetric body. In addition, the nonlinear aerodynamic loads have been distributed over the body and lifting surfaces to provide a more useful tool for preliminary structural analysis. Finally, new technology was developed to improve the prediction of axial force at angle of attack (AOA). These new technologies have been integrated into the AP95 and will be transitioned to legitimate users as the AP98. To make the AP98 more user friendly, an upgraded pre- and post-processing, personal computer interface was also developed. Comparisons of the new theory have been made to both experimental data and the AP95. Comparisons of theory and experiment show the AP98 to be at least as good as the AP95 and, in general, maybe slightly better. In general, average accuracy levels of aerodynamics are +/- 10 percent on axial and normal force and +/- 4 percent of body length on center of pressure. For nonaxisymmetric body cases, accuracy can be slightly higher than these numbers, although not enough cases have been considered to make a definitive assessment. While these accuracy levels are encouraging for a semiempirical code, they could be improved upon by use of computational fluid dynamics codes or additional experimental data or both to reduce errors due to limited data bases.


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